---
title: "MariaDB Analytics Tutorial: 5 Steps to Get Started in 10 Minutes"
publish_date: 2017-05-11
updated_date: 2020-08-10
author: "MariaDB"
tags:
  - name: "Analytics"
    url: "/resources/blog/tag/analytics.md"
  - name: "Big Data"
    url: "/resources/blog/tag/big-data.md"
  - name: "Business"
    url: "/resources/blog/tag/business.md"
  - name: "Clustering"
    url: "/resources/blog/tag/clustering.md"
  - name: "ColumnStore"
    url: "/resources/blog/tag/columnstore.md"
  - name: "Community"
    url: "/resources/blog/tag/community.md"
  - name: "DBA"
    url: "/resources/blog/tag/dba.md"
  - name: "Developer"
    url: "/resources/blog/tag/developer.md"
  - name: "High Availability"
    url: "/resources/blog/tag/high-availability.md"
  - name: "How to"
    url: "/resources/blog/tag/how-to.md"
  - name: "MariaDB Enterprise"
    url: "/resources/blog/tag/mariadb-enterprise.md"
  - name: "MariaDB Releases"
    url: "/resources/blog/tag/mariadb-releases.md"
  - name: "MaxScale"
    url: "/resources/blog/tag/maxscale.md"
  - name: "MySQL"
    url: "/resources/blog/tag/mysql.md"
  - name: "Security"
    url: "/resources/blog/tag/security.md"
---

# MariaDB Analytics Tutorial: 5 Steps to Get Started in 10 Minutes

Looking for an easy way to get started with analytics? MariaDB ColumnStore provides a simple, open and scalable analytics solution. It leverages a pluggable storage engine to handle analytic workloads while keeping the same ANSI SQL interface that is used across the MariaDB portfolio. This blog provides a quick 5-step tutorial to help you get started with MariaDB ColumnStore.

Before you begin, please download the sample dataset, including:

- [Raw dataset from Lending Club](https://www.lendingclub.com/info/download-data.action)
- [SQL script](https://www.dropbox.com/s/k7sebc6vpp76ei2/loans_demo_scripts.tar.gz?dl=0)

**Step 1: MariaDB ColumnStore Installation and Configuration**

In this step, you will learn how to [download](https://staging-mdb.com/downloads/columnstore) and install MariaDB ColumnStore.

**Step 2: Create Table and Load Data**

MariaDB ColumnStore does not require you to set up index and partitioning. It provides an easy way to create a table and load data without help from DBAs. In addition, when ColumnStore loads data, it uses cpimport which leverages parallel query loading capability. To learn more about cpimport, watch [this presentation](https://m17.mariadb.com/node/28) by our solutions engineer, Anders Karlsson.

**Step 3: Create Dimension Table / Cross Engine Join**

Leveraging the MariaDB Server interface, we can use “Dimension Tables” from the InnoDB storage engine and join those with the “Fact Table” data in ColumnStore. In this demo, we join a loan stats fact table and dimension table to create a sample quarterly report on loan amount.

**Step 4: Window Function**

Another benefit of ColumnStore is built-in analytics queries like window functions. Without writing complex code, users can run window functions in SQL to run time series analysis or run averages on a certain dataset. In this example, with one SQL query, you can report on the top ranked delinquent loan amounts in five specific states.

**Step 5: Data Visualization: Tableau integration**

ColumnStore provides an easy way to connect to third-party BI tools like Tableau using a generic [ODBC driver](https://staging-mdb.com/downloads/connector), enabling you to better visualize your data.

![CS blog.png](/sites/default/files/users/user59756/CS%20blog.png)

Hope you enjoyed the tutorial! Here are some additional resources to help you along the way:

- Cloud – [Deploy MariaDB ColumnStore with Amazon AMI ](https://staging-mdb.com/kb/en/mariadb/installing-and-configuring-a-columnstore-system-using-the-amazon-ami/)
- Container – [Deploy MariaDB ColumnStore on Docker or Vagrant ](https://staging-mdb.com/kb/en/mariadb/mariadb-columnstore-docker-vagrant-and-windows-10-linux-setup-allows-for-ev/)
- MariaDB ColumnStore Use Case – [Visual analysis of health data](https://m17.mariadb.com/node/152) by the Institute for Health Metrics and Evaluation (IHME)